tiltxcorr(1) General Commands Manual tiltxcorr(1)
NAME
tiltxcorr - to align a tilt series by cross-correlation
SYNOPSIS
tiltxcorr [options] input_file output_file
DESCRIPTION
Tiltxcorr uses cross-correlation to find an initial translational
alignment between successive images of a tilt series. For a given pair
of images, it stretches the image with the larger tilt angle perpendic-
ular to the tilt axis, by an amount equal to the ratio of the cosines
of the two tilt angles (cosine stretch). The stretched image is corre-
lated with the other image, and the position of the peak of the corre-
lation indicates the relative shift between the images. There are
options to use only a subset of the image, to pad the image with a bor-
der before correlating, and to taper the image intensities down to the
average level over some boundary region. The latter feature is partic-
ularly important for getting reliable correlation peaks. The program
also has an option to correlate each image with the sum of already-
aligned images at lower tilts, a method developed by Christian Renken.
In addition, the program can be used to track the centers of multiple
subareas through the tilt series and produce an IMOD model that can be
used for fiducial alignment. The program will reduce the size of
images larger than 1180 pixels in one dimension by binning them down,
i.e. by averaging the values in square sets of adjacent pixels (2x3, or
3x3, etc). Images are binned by the smallest factor needed to make
them 1180 or smaller up to a binning of 4, but there is option to set
the binning directly.
The program is also useful for cross-correlation alignment of untilted
images such as serial sections and subframes recorded when acquiring an
image from a direct electron detection camera.
Some notes about some of the options:
FILTERING: Some high pass filtering, using a small value of Sigma1 such
as 0.03, may be needed to keep the program from being misled by very
large scale features in the images. If the images are noisy, some low
pass filtering with Sigma2 and Radius2 is appropriate (e.g. 0.05 for
Sigma2, 0.25 for Radius2). If the images are binned, these values
specify frequencies in the binned image, so a higher cutoff (less fil-
tering) might be appropriate. The filter functions produced by these
options can be visualized with the program Filterplot; see that man
page for a full description of their effects.
SUBAREAS: Trimming some area off the edges of the images may be helpful
if those areas are particularly out of focus or contain material with
no useful features in it. The area to be used for correlation can be
offset from the center of the image by specifying starting and ending
coordinates of the region to correlate instead of the amount to trim
off. The coordinates should be chosen from the zero-tilt image; the
program will shift the specified box closer to the center of the image
at higher tilts so that it will contain approximately the same fea-
tures. By default, the transformations will be adjusted to move the
tilt axis back to the center of the whole image, but there is an option
to leave the axis at the center of the correlated area instead. Note
that global rather than image-to-image transforms are output in this
case; see below for details.
PADDING: Padding is customarily done to reduce the contribution to the
correlation from wrapped around features, which occurs when correlation
is done with Fourier transforms. Extensive padding does not help with
typical biological specimens but may be needed for specimens with peri-
odic structures, in which case one should pad each edge by half the
image size.
TAPERING: In contrast, tapering the images down to a mean intensity at
their edges is very important. Tapering over as few as 20 pixels may
be adequate, but fewer artifacts will appear in the correlation with
longer tapers (say, 50 to 100 pixels).
CENTRAL PEAK EXCLUSION: The exclusion of a central peak may be helpful
when there is fixed noise in the images due to inadequate gain normal-
ization of CCD camera images. Because one image is stretched, this
spurious peak can actually occur anywhere in an elongated region per-
pendicular to the tilt axis. As of IMOD 4.6.31, this option has become
much more reliable and effective, since a peak will be excluded only if
certain conditions are met. First, the program tests whether the peak
center is within 0.3 pixels of the center line of the elongated region,
whether this peak is narrower than the highest peak outside the exclu-
sion region in at least one direction, and whether that highest eligi-
ble peak is sufficiently stronger than the next-highest one. If these
tests are passed, the program computes a correlation between unbinned,
unstretched images with no high-frequency filtering and measures the
width of first and second peaks. If the first peak is narrow enough,
and sufficiently narrower than the second peak, then the highest eligi-
ble peak position (in the original correlation) is used.
CUMULATIVE CORRELATION: Tiltxcorr has an option to use a cumulative
correlation method developed by Christian Renken at the National Center
for the Visualization of Biological Complexity in Albany, N.Y. With
this option, the program will take the image at zero tilt as the first
reference, and correlate it with the image at the next most negative
tilt. It will then add the aligned image to the first reference to
make the reference for the next tilt. At each tilt, the reference will
be the sum of images that have already been aligned. When the most
negative tilt angle is reached, the procedure is repeated from the
zero-tilt view to more positove tilt angles. (If you specify a range
of views to correlate that does not pass through zero tilt, then this
procedure will start at the lowest tilt in the specified range.) There
are two options that can be used with this procedure. By default,
aligned images are not cosine-stretched before being added into the
cumulative reference; but the "absstretch" option will add images that
have been stretched by the inverse of the cosine of the tilt angle into
the reference. The "nostretch" option will disable the cosine stretch-
ing that is used before correlating an image with the reference.
180-DEGREE TILT SERIES: If the object being viewed is compact rather
than slab-like and it is tilted close to 90 degrees, then the cosine
stretching between views is not appropriate. Use the "nostretch"
option in this case. With this option, the program will also not
attempt to adjust the shifts between images to keep the tilt axis in
the center, a procedure which fails close to 90 degrees.
TRACKING PATCHES: In a completely different mode of operation, the pro-
gram can track the center positions of multiple subareas (patches)
through the tilt series and produce an IMOD model. There is no feature
detection involved here, so the alignment of patches from two succes-
sive views is averaged over all the image features in the patch. Patch
tracking is invoked by entering the -size option to specify the size of
the patches. The positions of the patches are specified by entering
the number of patches in X and Y, or by providing a model with scat-
tered points indicating the positions of the patch centers. In the
latter case, the points may be on any view, but their positions will be
transferred by cosine stretching to the view nearest to zero tilt, and
the tracking will start at that view. Note that patches smaller than
1180 pixels will be correlated without binning by default, whereas the
whole image will typically be binned for correlation. As a result, the
patch correlations may be noisier and may require either more high-fre-
quency filtering or explicit binning. If views are skipped, there will
be no model points on those views and positions will be tracked between
the views before and after a skipped view. If the transforms used for
preliminary alignment of the input stack are supplied, then the program
will be able to detect when patches contain blank image area. It will
either skip a patch when it has too much blank area (more that 30%), or
it will taper the image data down to the edge of the blank area to min-
imize correlation artifacts. When a patch is skipped on a view, the
tracking will be resumed on the next view where the patch has usable
image data, unless more than 5 views have been skipped.
FINDING WARPING TRANSFORMATIONS: In a variation on patch tracking, the
program can output the local patch displacements as a set of warping
transformations that align each section to the previous one. This fea-
ture is not for tilt series but for other serial images that need to be
aligned with warping. With tilt series patch tracking, the tracking
area moves through the views to follow a piece of image, whereas when
finding warp transformations, the tracking area is in the same position
on every section, either on a regular grid or as defined by a seed
model. The format of warping transformations is described in the docu-
mentation for library libiwarp.
BOUNDARY CONTOURS: Boundary contours may be used to constrain the
region being correlated for alignment or the locations tracked by cor-
relation. When used with tilt series, contours may be drawn on any
view but they will be stretched by 1/cosine of the tilt angle to deter-
mine their position on the zero-tilt view. When correlating whole
images to obtain transforms, the boundary contours are used in two
ways. First, the minimum rectangular area containing the contours at
zero tilt is determined; this area is limited by the -border, -xminmax
and -yminmax options to define the area that will be used for correla-
tion. Second, on each view, the contours are contracted from their
positions at zero tilt by the cosine of the tilt angle, and the area
outside the contours is masked out by setting it to the image mean.
The masked image is correlated with an unmasked image at the previous
tilt. Multiple contours may be drawn, and they may intersect. If
there is only one contour, the image intensity inside the unmasked
region is tapered down to the mean at the edge over the course of 16
pixels, equivalent to running Mrctaper on the image. This tapering
may help prevent artifacts due to sharp edges, but it is not done if
there is more than one contour. If tapering and the inclusion of sepa-
rated areas are both important, use a single contour with a narrow con-
nector between them, but take care that the contour does not cross
itself.
Boundary contours are used differently when correlating to track the
centers of patches. For a tilt series, the program determines the
fraction of each patch that is within any of the contours (where all
contours are projected onto the zero tilt view), and then eliminates
patches whose fractions are less than 0.75. There is no masking of the
image regions that fall outside the boundaries in this case. When
finding warping transformations, the boundary contour used at a partic-
ular section is taken from the nearest section with a boundary contour.
Thus, it is useful to draw boundary contours at multiple sections in
the stack, whenever the region suitable for tracking changes. The
patches are evaluated for inclusion separately on every section, using
the contours appropriate for that section.
OPTIONS
Tiltxcorr uses the PIP package for input (see the manual page for
pip) and can still take sequential input interactively, to maintain
compatibility with old command files. The following options can be
specified either as command line arguments (with the -) or one per line
in a command file or parameter file (without the -). Options can be
abbreviated to unique letters; the currently valid abbreviations for
short names are shown in parentheses.
-input(-inp) OR -InputFileFilename
Input file with images to correlate. If this option is not
entered, the first non-option argument will be used for this
input file.
-piece(-pi) OR -PieceListFileFilename
Piece list file for reordering the Z values in the stack
-output(-ou) OR -OutputFileFilename
Output file for transformations or for patch tracking model. If
this option is not entered, the second non-option argument will
be used for this input file.
-rotation(-ro) OR -RotationAngleFloatingpoint
Angle of rotation of the tilt axis in the images; specifically,
the angle from the vertical to the tilt axis (counterclockwise
positive).
-first(-f) OR -FirstTiltAngleFloatingpoint
Tilt angle of first view, in degrees. Use this option together
with TiltIncrement.
-increment(-inc) OR -TiltIncrementFloatingpoint
Increment between tilt angles, in degrees. Use this option
together with FirstTiltAngle.
-tiltfile(-ti) OR -TiltFileFilename
Use this option if tilt angles are in a file, one per line.
-angles(-ang) OR -TiltAnglesMultiplefloats
Use this option to enter the tilt angles for each view individu-
ally, in degrees. (Successive entries accumulate)
-offset(-of) OR -AngleOffsetFloatingpoint
Amount to add to all entered tilt angles. If the specimen is
significantly tilted at zero tilt, then the amount of cosine
stretching become inaccurate at high tilt. Sharper correlations
can be obtained by adding this angle offset, which is the same
as the offset needed in Tiltalign or Tilt to make the
specimen flat in the reconstruction.
-reverse(-rev) OR -ReverseOrder
Reverse order of processing when all views have same tilt angle.
Specifically, this will cause the program to start with the last
view at minimum tilt instead of the first one.
-radius1 OR -FilterRadius1Floatingpoint
Low spatial frequencies in the cross-correlation will be attenu-
ated by a Gaussian curve that is 1 at this cutoff radius and
falls off below this radius with a standard deviation specified
by FilterSigma2. Spatial frequency units range from 0 to 0.5.
Use FilterSigma1 instead of this entry for more predictable
attenuation of low frequencies.
-radius2 OR -FilterRadius2Floatingpoint
High spatial frequencies in the cross-correlation will be atten-
uated by a Gaussian curve that is 1 at this cutoff radius and
falls off above this radius with a standard deviation specified
by FilterSigma2.
-sigma1 OR -FilterSigma1Floatingpoint
Sigma value to filter low frequencies in the correlations with a
curve that is an inverted Gaussian. This filter is 0 at 0 fre-
quency and decays up to 1 with the given sigma value. However,
if a negative value of radius1 is entered, this filter will be
zero from 0 to |radius1| then decay up to 1.
-sigma2 OR -FilterSigma2Floatingpoint
Sigma value for the Gaussian rolloff below and above the cutoff
frequencies specified by FilterRadius1 and FilterRadius2
-exclude(-e) OR -ExcludeCentralPeak
Exclude a central correlation peak caused by fixed pattern noise
in the images. In tilted images, these peaks can occur anywhere
within an extended, narrow strip perpendicular to the tilt axis.
A peak in this region will now be excluded only if conditions
are met both by this peak and by the highest peak outside this
region, as described above.
-central(-ce) OR -CentralPeakExclusionCriteriaThreefloats
This option specifies three of the criteria applied when decid-
ing whether to exclude a peak at (0, 0): the minimum ratio of
the second to the third peak strength (default 3); the absolute
width of the central peak in the unbinned, unstretched correla-
tion (default 1.5); and the minimum ratio of the second to the
first peak width (default 1.6).
-shift(-sh) OR -ShiftLimitsXandYTwointegers
Limits on distance in X and Y to search for correlation peak, in
pixels before binning is applied internally. This option can be
used to prevent a spurious correlation peak outside these limits
from giving a bad alignment. As of IMOD 4.6.31, the peak must
be located within an ellipse whose axes are defined by the lim-
its in X and Y. If the program does not find an actual peak,
i.e. a pixel higher than all its neighbors, within these limits,
then it will give a zero shift. If cumulative correlations are
being used, the program will seek a peak within this distance of
the peak for the previous view and assign that view's shift
instead of zero if no peak is found.
-rect(-rec) OR -RectangularLimits
With this option, the -shift option works as it did before IMOD
4.6.31, requiring a peak to be within the rectangle defined by
the limits in X and Y.
-ccc(-cc) OR -CorrelationCoefficient
Compute a normalized cross-correlation coefficient at the 10
highest correlation peaks and pick the peak with the highest
coefficient. This computation requires 5 Fourier transforms
instead of 3, because filtered images must be used for computing
the correlation coefficient.
-border(-bor) OR -BordersInXandYTwointegers
Number of pixels to trim off each edge in X and in Y (the
default is to use the whole image).
-xminmax(-x) OR -XMinAndMaxTwointegers
Starting and ending X coordinates of a region to correlate,
based on the position of the region at zero tilt. This entry
will override an X border value entered with BordersInXandY.
-yminmax(-y) OR -YMinAndMaxTwointegers
Starting and ending Y coordinates of a region to correlate.
This entry will override a Y border value entered with Border-
sInXandY.
-boundary(-bou) OR -BoundaryModelFilename
Model file with boundary contours around areas to correlate.
When correlating whole images to obtain transforms, the area
outside the contours is masked out; when tracking patches, only
patches inside the contours will be tracked (see above for
details).
-objbound(-objb) OR -BoundaryObjectInteger
The number of the object to use from the model with boundary
contours. The default is to use all the contours in closed-con-
tour objects, but with this option only the given object will be
used.
-binning(-bi) OR -BinningToApplyInteger
Binning or other reduction to apply to the trimmed, padded
images. Ordinary binning is used unless the -antialias option
is given. By default, a reduction will be selected that makes
the maximum dimension of the trimmed, padded image be no more
than 1250 pixels, up to a reduction of 4. Reduction will be
increased above 4 only to the extent needed to make the image
fit in the arrays. This default behavior might result in more
reduction than desired, and the reduction might change when the
amount of trimming is changed. This option allows direct con-
trol of the reduction instead.
-antialias(-ant) OR -AntialiasFilterInteger
Type of antialiasing filter to use for image reduction instead
of binning. Antialiasing becomes important when the images con-
tain a strong noise component at the high frequencies being
eliminated by the image reduction. Ordinary binning reduces
aliasing, but not as much as these filters do. As in New-
stack(1), the available types here are:
2: Blackman - fast but not as good at antialiasing as slower
filters
3: Triangle - fast but smooths more than Blackman
4: Mitchell - good at antialiasing, smooths a bit
5: Lanczos 2 lobes - good at antialiasing, less smoothing
than Mitchell
6: Lanczos 3 lobes - slower, even less smoothing but more
risk of ringing
-leaveaxis(-lea) OR -LeaveTiltAxisShifted
Leave the tilt axis in the center of the region that was corre-
lated; the default is to shift it back to the center of the
whole image. With this option, the program will output global
transforms ready to use in Newstack, rather than the trans-
forms relating one view to the next that would need to be con-
verted to global transforms with Xftoxg. The reason for this
difference is that the transforms must contain a net shift away
from the center of the image, which would be lost in Xftoxg.
-pad OR -PadsInXandYTwointegers
Number of pixels to pad images on each side in X and in Y,
before binning. With no padding, shifts greater than 50% of the
image size will not be treated correctly. Each 1% of padding
allows proper treatment of shifts more than 50% by an additional
2% of image size. The default is 5% of images dimensions for
patch tracking or finding warping, or 10% for regular correla-
tions, allowing shifts up to 70% of the image size to be deter-
mined.
-taper(-ta) OR -TapersInXandYTwointegers
Number of pixels to taper images in X and in Y. The default is
10% of the image dimensions.
-views(-vi) OR -StartingEndingViewsTwointegers
Starting and ending view numbers, numbered from 1, for doing a
subset of views.
-skip(-sk) OR -SkipViewsListofintegerranges
List of views to skip, while maintaining alignment across
skipped views. The program will not find the transform for
aligning a listed view to the previous one. When a view is
skipped, the following view will be aligned to the last
unskipped view and a unit transform will be output for the
skipped view. With patch tracking, no model points will be
placed on the skipped views. Comma-separated ranges of views
(numbered from 1) can be entered. The default is to use all of
the views.
-break(-br) OR -BreakAtViewsListofintegerranges
List of views to break alignment at. This option is like
"-skip" in that no transform is found for aligning a listed view
to the previous one and a unit transform is written for the
listed view. However, the following view will be aligned to the
listed view, and nothing will be aligned to the previous view.
This breaks the chain of alignment through the series of views.
This option cannot be used with tilt series patch tracking, but
can be used when finding warping.
-cumulative(-cu) OR -CumulativeCorrelation
Use this option to add up previously aligned pictures to get the
reference for the next alignment. Alignments will start at low
tilt and work up to high tilt.
-absstretch(-ab) OR -AbsoluteCosineStretch
Stretch each image added into the cumulative sum by 1 over the
cosine of its tilt angle.
-nostretch(-no) OR -NoCosineStretch
Do not do any cosine stretching for correlations or for accumu-
lating into the reference (this option overrides Absolute-
CosineStretch).
-iterate(-it) OR -IterateCorrelationsInteger
Number of iterations of the correlation. After finding the
pixel with the peak correlation, the program achieves subpixel
accuracy by fitting a parabola to the correlation values in X or
Y and interpolating from the parabola. If the correlation is
iterated, this subpixel shift is applied to the cosine-stretched
image before the correlation, which tends to shift the peak to
being exactly on a pixel. As a result, the shift has slightly
higher subpixel accuracy than when it is derived by parabolic
interpolation. The program will terminate the iterations if the
remaining fractional shift is less than 0.02 pixel or if a lower
correlation value is obtained than on the previous iteration.
In the latter case it reverts to the shift that gave the highest
correlation. Two or three iterations are generally sufficient.
Iteration is not programmed efficiently, so computation time
will be proportional to the number of iterations.
-search(-sea) OR -SearchMagChanges
Search for the magnification factor that gives the highest cor-
relation coefficient at one or more views. This factor will be
incorporated into the transformation for the respective view.
If a maximum value of the correlation coefficient is not found
within the allowed range (specified with the -mag option), a
magnification of 1 is used. This option cannot be used together
with rotation scan, cumulative correlation, patch tracking, or
when finding warping.
-changes(-ch) OR -ViewsWithMagChangesListofintegerranges
List of views at which to search for magnification changes.
Ranges are allowed. The default is to do all views.
-mag(-m) OR -MagnificationLimitsTwofloats
Lower and upper limits for size change when searching for magni-
fication factors. The default is 0.9,1.1.
-scan(-sc) OR -ScanRotationMaxAndStepTwofloats
Either the maximum angle and angular step size at which to apply
rotation in order to estimate the best rotation; or a single
rotation angle to apply and a 0 step size. With a positive step
size to estimate rotation, the program does a coarse scan just
at the given interval from the negative to positive maximum
angle, then estimates the best rotation by interpolation. This
is unlike the magnification search, which reduces its step size
to refine the estimate. The final correlation is done at the
interpolated angle. With a step size of 0, the angle given as
the maximum (which can be negative) is applied before correlat-
ing. The resulting transformation incorporates the rotation in
either case. This option cannot be used together with magnifi-
cation search, cumulative correlation, patch tracking, or when
finding warping.
-reference(-ref) OR -ReferenceFileFilename
Input file containing an image to use as a reference. Each view
from the main input image file will be aligned with this refer-
ence image, which will be assumed to be at zero tilt. The out-
put file will contain a linear transform for every view in the
input file; if a subset of views is specified with -views or
some views are skipped, unaligned views will be given a unit
transform. This option cannot be used with cumulative correla-
tions, patch tracking, or when finding warping.
-rview(-rv) OR -ReferenceViewInteger
View number of image to use in reference file, numbered from 1.
-size(-siz) OR -SizeOfPatchesXandYTwointegers
Size in X and Y of patches to track by correlation. This option
will cause the program to track a set of patches of the given
size from the starting view to the high tilt view in each direc-
tion, and to output the positions of the patch centers in an
IMOD model. By default, patches will overlap in each direction
by the default value for the -overlap option (see below). You
can change the overlap with the -overlap option, specify the
number of patches directly with the -number option, or enter a
model of points to track with the -seed option, but you can
enter only one of these options. Patch tracking cannot be used
with cumulative correlation.
-number(-nu) OR -NumberOfPatchesXandYTwointegers
Number of patches in X and Y to track by correlation. The given
number of patches will be regularly spaced apart and fill the X
and Y ranges of the trimmed image area.
-overlap(-ov) OR -OverlapOfPatchesXandYTwointegers
Fractional overlap in X and Y between patches that are tracked
by correlation. These overlaps are used to determine the number
of patches when -number is not entered. The default, 0.33,
0.33, which will make patches that overlap by one-third in each
direction. A value of 0 will result in no overlap, and values
less than 0 will result in space between the patches.
-seed(-see) OR -SeedModelFilename
Input model file with center points to track by correlation.
Only points whose patches fit entirely within the trimmed image
area at zero degrees will be tracked. See above for details.
-objseed(-objs) OR -SeedObjectInteger
Number of the object from the seed model with the points for
tracking patches. The default is to use all objects containing
scattered points; with this option only the given object will be
used.
-length(-len) OR -LengthAndOverlapTwointegers
When tracking patches by correlation, the default is to produce
one contour per patch passing through the whole set of views.
With this option, the contour will be broken into pieces of the
given length, and overlapping by at least the given amount. If
the centers of the tracked areas wander enough to give a bad fit
when the resulting model is used in Tiltalign, then breaking
the contours into overlapping pieces might improve the fit.
Some overlap is needed to use the model in Tiltalign (1).
-prexf(-pr) OR -PrealignmentTransformFileFilename
File with transformations applied to align the images being used
for patch tracking. With the shift information in these trans-
forms, each patch is evaluated for whether it contains blank
image area because of the shifting. Patches that are more than
30% blank will not be tracked further, and patches with some
blank area less than this amount will be tapered down to the
edge of the blank area.
-imagebinned(-im) OR -ImagesAreBinnedInteger
The current binning of the images relative to the unaligned
stack. This entry is needed to scale the transforms supplied
with the -prexf option if the binning is not 1.
-unali(-un) OR -UnalignedSizeXandYTwointegers
The full size of the unaligned stack that was transformed to
create the images being aligned with patch tracking. This entry
is needed if an output size was specified when creating the
stack being aligned and if transforms are supplied with the
-prexf option.
-warp(-w) OR -FindWarpTransformsInteger
Use patch correlations to find and save warping transformations
between successive images. The output file will be a file with
warp transforms, not a model. Enter 1 for transforms with the
linear component separated out, and -1 to not separate the lin-
ear component. Tilt angles cannot be entered with this option,
nor can the -reverse option. Unlike with tilt series patch
tracking, you can break the alignment at views as well as skip
views. Limits in X and Y and a boundary model can be used to
constrain patch locations, but there must be at least 3 patches
in the area defined by all the boundary contours.
-pair(-pai) OR -RawAndAlignedPairTwointegers
After transforms relating each section to the previous have been
obtained, this option can be used to find a warping alignment
between a pair of sections, where the first is an unaligned
image and the second is a section transformed into linear align-
ment with it. The option specifies the view number (numbered
from 1, as usual) of the second view of the pair and the total
number of sections. If this option is entered, the file of sec-
tion-to-section transforms must be entered with the -prexf
option. The input images must not be binned or resized from the
ones on which those transforms are based. This option is used
by Xfalign.
-append(-ap) OR -AppendToWarpFile
When doing a raw and aligned pair, this option can be used to
add the warp transform from the pair to an existing file. The
output file must be a valid warp transform file.
-test(-te) OR -TestOutputFilename
Specify a filename with this option to have two padded, tapered
images and the cross-correlation saved for every pair of images
that are correlated.
-verbose(-ve) OR -VerboseOutput
Output diagnostic information
-param(-par) OR -ParameterFileParameterfile
Read parameter entries as keyword-value pairs from a parameter
file.
-help(-h) OR -usage
Print help output
-StandardInput
Read parameter entries from standard input.
INTERACTIVEINPUT
If there are no command-line arguments, Tiltxcorr takes sequential
input the old way, with the following entries:
Image input file
Piece list file for reordering the Z values in the stack, or Return if
none
Output file for F transforms
-1 to enter individual tilt angle for each view, 1 to specify a start-
ing and increment tilt, or 0 to read tilt angles from a file
IF you entered 1, next enter the starting and incremental tilt angles
IF you entered -1, enter the tilt angle of each view.
IF you entered 0, enter name of file with tilt angles
Angle of rotation of the tilt axis in the images; specifically, the
angle from the vertical to the tilt axis (counterclockwise positive).
Filter parameters to filter the correlation, or / for no filter (Enter
values of Sigma1, Sigma2, Radius1, Radius2 just as for ENHANCE.)
1 to exclude a central correlation peak due to fixed pattern noise in
the images, or 0 not to
Number of pixels to trim off each side in the X and Y dimensions, or /
to use the whole image area
Borders (in pixels) with which to pad images in the X and Y dimensions,
or / for the default, which is 5% of the image dimensions up to 20 pix-
els
Distances in pixels over which to taper image intensities down to the
mean at the edges, in the X and Y dimensions. Enter / for the default,
which is 10% of the image dimensions up to 100 pixels
Starting and ending view #'s (first is 1), or / for all views
HISTORY
Written by David Mastronarde 10/6/98
BUGS
Email bug reports to mast at colorado dot edu.
IMOD 4.10.12 tiltxcorr(1)